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Machine learning, infection, microbial toxins profile and health monitoring pre/post general surgeries during COVID-19 pandemic
Abstract
Although almost 2 years have passed since the beginning of the coronavirus disease 2019 (COVID-19) pandemic in the world, there is still a threat to the health of people at risk and patients. Specialists in various sciences conduct various research in order to eliminate or reduce the problems caused by this disease. Surgery is one of the sciences that plays a critical role in this regard. Both physicians and patients should pay attention to the potent steps of different infections’ key-points during pre/post-general surgeries in the case of preventing or accelerating the healing process of nosocomial acquired COVID-19. The relationship between COVID-19 and general surgical events is one of the factors that could directly or indirectly play a key role in the body's resilience to COVID-19. In this article, we introduce a link between pre/post-general surgery steps, human microbial toxin profiles, and the incidence of acquired COVID-19 in patients. In linking the components of this network, artificial intelligence (AI), machine learning (ML) and data mining (DM) can be important strategies to assist health providers in choosing the best decision based on a patient’s history.
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